Triple
T22918344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mountain Dew |
E568790
|
entity |
| Predicate | typicalCaffeineContentPer12flOz |
P38318
|
FINISHED |
| Object | 54 mg |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 54 mg | Statement: [Mountain Dew, typicalCaffeineContentPer12flOz, 54 mg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCaffeineContentPer12flOz Context triple: [Mountain Dew, typicalCaffeineContentPer12flOz, 54 mg]
-
A.
typicalCaffeineSource
Indicates that one entity is a common or characteristic source from which the other entity typically obtains caffeine.
-
B.
hasCaffeineContent
chosen
Indicates that one entity (typically a beverage or substance) possesses a specified amount or presence of caffeine.
-
C.
carbohydratesPer12Ounces
Indicates the amount of carbohydrates contained in a 12-ounce serving of a given item.
-
D.
isSoftDrinkVariantOf
Indicates that one soft drink is a specific version, flavor, or formulation derived from or based on another soft drink.
-
E.
isSoftDrink
Indicates that something is classified as a soft drink, typically a non-alcoholic, carbonated or sweetened beverage.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1807b254c8190bb84596dcacaa35e |
completed | April 29, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:42 p.m.